Biomedical subjects

Peter J Campbell

Publications and source records attributed to Peter J Campbell.

4 recordsLinked to original sources

PubMed2026

Neocentromeres fail to maintain DNA methylation boundaries, driving CENP-A drift, instability, and chromosome missegregation.

Centromere identity is specified by CENP-A, a histone H3 variant that epigenetically defines centromere position. How CENP-A is maintained at one location in rapidly evolving centromeric DNA is unknown. Using single-cell-derived clones of human cell lines, we demonstrate heterogeneity in CENP-A position within cell populations at neocentromeres and a native centromere. CENP-A heterogeneity is accompanied by heterogeneous DNA methylation patterns, with DNA methylation shifting according to CENP-A position. We demonstrate centromere epigenetic plasticity over extended proliferation, with native centromeres maintaining stable DNA methylation boundaries, but neocentromeres exhibiting DNA methylation instability, boundary loss, and increased missegregation. Finally, we show that neocentromeres are more sensitive to DNA methylation inhibition than native centromeres, and that this inhibition is accompanied by expanded CENP-A-enriched domains and increased missegregation. This study supports a role for DNA methylation boundaries in maintaining centromere position, stability, and function and highlights the intrinsic instability of DNA methylation at neocentromeres.

CENP-A↗

PubMed2025

A dedicated caller for DUX4 rearrangements from whole-genome sequencing data.

Rearrangements involving the DUX4 gene (DUX4-r) define a subtype of paediatric and adult acute lymphoblastic leukaemia (ALL) with a favourable outcome. Currently, there is no 'standard of care' diagnostic method for their confident identification. Here, we present an open-source software tool designed to detect DUX4-r from short-read, whole-genome sequencing (WGS) data. Evaluation on a cohort of 210 paediatric ALL cases showed that our method detects all known, as well as previously unidentified, cases of IGH::DUX4 and rearrangements with other partner genes. These findings demonstrate the possibility of robustly detecting DUX4-r using WGS in the routine clinical setting.

Humans↗

PubMed2025

Implementing Mutational Epidemiology on a Global Scale: Lessons from Mutographs.

The Mutographs Cancer Grand Challenge team aimed to discover unknown causes of cancer through mutational epidemiology, an alliance of cancer epidemiology and somatic genomics. By generating whole-genome sequences from thousands of cancers and normal tissues from more than 30 countries on five continents, it discovered unsuspected mutagenic exposures affecting millions of people, raised the possibility that some carcinogens act by altering forces of selection in tissue microenvironments rather than by mutagenesis, and demonstrated changes to the direction of somatic evolution in normal cells of the human body in response to exogenous exposures and noncancer diseases. See related article by Bressan et al., p. 16 See related article by Bhattacharjee et al., p. 28 See related article by Goodwin et al., p. 34.

Humans↗

PubMed2021

Whole-genome sequencing reveals progressive versus stable myeloma precursor conditions as two distinct entities.

Multiple myeloma (MM) is consistently preceded by precursor conditions recognized clinically as monoclonal gammopathy of undetermined significance (MGUS) or smoldering myeloma (SMM). We interrogate the whole genome sequence (WGS) profile of 18 MGUS and compare them with those from 14 SMMs and 80 MMs. We show that cases with a non-progressing, clinically stable myeloma precursor condition (n = 15) are characterized by later initiation in the patient's life and by the absence of myeloma defining genomic events including: chromothripsis, templated insertions, mutations in driver genes, aneuploidy, and canonical APOBEC mutational activity. This data provides evidence that WGS can be used to recognize two biologically and clinically distinct myeloma precursor entities that are either progressive or stable.

DNA Copy Number Variations↗